Method for rendering digital radiographic images for display based on independent control of fundamental image quality parameters

ABSTRACT

A method of enhancing a digital image comprising: providing a digital image; decomposing the provided digital image into a multi-frequency band representation including a low frequency band image and multiple different high frequency band images; multiplying each of the high-frequency band images with a gain factor; summing together the unmodified low frequency band image and the modified high-frequency band images to produce a reconstructed digital image; and mapping the reconstructed digital image through a tone-scale look-up-table to map the reconstructed digital image to optical densities

FIELD OF THE INVENTION

This invention relates in general to image enhancement in digital imageprocessing and in particular, to a method of image enhancement to beused in a medical radiographic imaging system, such as a computedradiography system.

BACKGROUND OF THE INVENTION

It is a common desire to enhance images acquired from imaging devices toimprove their image quality. There are fundamental attributes thatgovern the image quality of a grayscale image. These attributes are thebrightness of an image, the dynamic range of an image, the contrast ofdetail in an image (or detail contrast), the sharpness of edges in animage, and the appearance of noise in an image. It is beneficial toprovide a system that enables direct and independent control of theseattributes of image quality. Further a system, which enables the controlof the detail contrast, sharpness, and noise appearance in a densitydependent fashion is also beneficial.

U.S. Pat. No. 5,805,721, inventors P. Vuylsteke and E. Schoeters,entitled “Method and Apparatus for Contrast Enhancement”, issued Sep. 8,1998 describes a multi-resolution method for enhancing contrast withincreased sharpness that includes dynamic range compression, andenhancing contrast without remarkably boosting the noise component. Thedescribed invention enhances detail contrast and sharpness via amulti-resolution method and controls dynamic range compression with agradation curve to map the processed image into the appropriate dynamicrange for the display. Application of the gradation curve will impactboth the apparent detail contrast and dynamic range of the displayedimage. Hence, both the modifying functions of the multi-resolutionprocessing and the shape of the gradation curve affect the detailcontrast in the image. This requires that both be adjusted when settingthe detail contrast in the image.

U.S. Pat. No. 5,978,518, inventors Oliyide et al., entitled “ImageEnhancement in Digital Image Processing”, issued Nov. 2, 1999 and U.S.Pat. No. 6,069,979 (continuation-in-part of U.S. Pat. No. 5,978,518),inventor VanMetter, entitled “Method for Compressing the Dynamic Rangeof Digital Projection Radiographic Images”, issued May 30, 2000,describe a multi-resolution method for performing dynamic rangemodification and high-frequency enhancement (including detail contrast).The methods include a tone scale look-up-table that is used to map theimage for display rendering. A tone scale look-up-table impacts thedynamic range and contrast of detail in an image. Hence, in this method,the dynamic range and detail contrast of the image depends on both thesettings of the frequency modification and the parameters of the tonescale look-up table. It is desirable, instead to have a single set ofparameters that control these attributes independently.

U.S. Pat. No. 6,072,913, inventor M. Yamada, entitled “Image ProcessingMethod and Apparatus”, issued Jun. 6, 2000, describes a multi-resolutionmethod for enhancing frequencies with dynamic range compression. Thedescribed invention requires the definition of many functions to controlthe performance of the algorithm. It does not disclose a set ofparameters that directly and independently control all of thefundamental attributes of image quality.

Thus, there is a need for a method that can be applied to an image, theparameters of which provide direct and independent control of the abovestated fundamental attributes of image quality.

SUMMARY OF THE INVENTION

According to the present invention, there is provided a solution to theproblems and fulfillment of the needs discussed above by means of amethod of digital image enhancement, especially image enhancement ofmedical diagnostic (radiographic) digital images.

According to a feature of the present invention, there is provided amethod for enhancing an image: providing a digital image; decomposingthe image into a multi-frequency band representation including a lowfrequency band image and multiple different high frequency band images;multiplying each of the high frequency band images with a gain factor;summing together the unmodified low frequency band image and themodified high-frequency band images to produce a reconstructed digitalimage: and mapping the reconstructed image through a tone scalelook-up-table to map it to optical densities.

ADVANTAGEOUS EFFECT OF THE INVENTION

The invention has the following advantages.

1. A method for independently controlling fundamental attributes ofimage quality of a digital image.

2. A method for controlling detail contrast, sharpness, and noiseappearance as a function of log exposure of a digital image is provided.

3. A method for density-dependent control of detail contrast, sharpnessand noise appearance of a digital image is provided.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a flow diagram of an embodiment of the present invention.

FIG. 2 is a graphical view showing an example of tone scale function andparameters useful in explaining the present invention.

FIG. 3 is a diagrammatic view illustrating the brightness control usedin the present invention.

FIG. 4 is a diagrammatic view illustrating the effect of increasing theslope of the tone scale useful in explaining the present invention.

FIG. 5 is a diagrammatic view illustrating the independent control ofdetail contrast vs. dynamic range in the present invention.

FIGS. 6 a-6 c are graphical views of functions to control detail,contrast, sharpness, and fine detail, respectively according to thepresent invention.

FIGS. 7 a-7 c are graphical views of log exposure dependent functions tocontrol detail contrast, sharpness, and fine detail, according to thepresent invention respectively.

FIG. 8 is a graphical view showing the mapping of density breakpoints tolog exposure break points according to the present invention.

FIG. 9 is a diagrammatic view of density dependent control of the detailcontrast according to the present invention.

FIG. 10 is a flow diagram of another embodiment of the presentinvention.

FIG. 11 is a block diagram of a digital image enhancement system forcarrying out the present invention.

DETAILED DESCRIPTION OF THE INVENTION

Referring now to FIG. 1, there is shown a block diagram of the presentinvention. A digital image in which code value is linearly related tolog exposure is captured with an image acquisition unit 10. Unit 10 canbe for example, a medical image acquisition unit such as, a diagnosticimage unit (MRI, CT, PET, US, etc.), a computed radiography or directdigital radiography unit, an x-ray film digitizer, or the like. Anyother digital image acquisition unit can also be used). The presentinvention processes the log exposure code value data, as shown in FIG.1, accordingly, the digital image data is split into four frequencybands B₀(i,j), B₁(i,j), B₂(i,j), and B₃(i,j). The log exposure codevalue data I(i,j) of the input digital input digital image is firstprocessed by three different low-pass filter operators 20, 30, 40. Eachoperator uses a square-wave filter. It will be evident to those skilledin the art that other low-pass filter shapes such as a triangle-filtercan be used. The filter kernel sizes are chosen to manipulate differentsized features (or different frequency ranges) in the image. The firstlow-pass filter operator 20 uses kernel K₀. This operator uses thelargest kernel size and it passes only the lowest frequencies. Itgenerates the low-pass image I₀(i,j). The next low-pass operator 30 useskernel K₁. This operator uses the next largest kernel size and it passesthe low to mid frequencies. It generates the low-pass image I₁(i,j). Thefinal low-pass operator 40 uses kernel K₂. This operator uses thesmallest kernel size and it passes all frequencies except for the veryhighest. It generates the low-pass image I₂(i,j). The low-pass imagesare used to generate the frequency bands. The lowest frequency bandimage is B₀(i,j) and is equal to I₀(i,j). This band representslarge-sized features in the image (and contains the lowest frequencies).Manipulation of this band produces a change in dynamic range orlatitude. The next frequency band B₁(i,j)=I(i,j)−I₀(i,j) is generated bysubtractor 60. This band contains the low-to-mid frequencies andrepresents mid-sized features in the image. Manipulation of this bandproduces a contrast effect without affecting the overall dynamic range.The next frequency band B₂(i,j)=I₂(i,j)−I₁(i,j) is generated bysubtractor 70. This band contains the mid-to-high frequencies andrepresents the small-sized features in the image. Manipulation of thisband produces a sharpness or blurring effect of the small-sizedfeatures. The next frequency band B₃(i,j)=I(i,j)−I₂(i,j) is generated bysubtractor 80. This band contains the highest frequencies in the imageand represents very fine detail in the image. Manipulation of this bandproduces a sharpness or blurring effect of very fine detail in theimage.

As shown further in FIG. 1, the higher frequency bands B₁(i,j), B₂(i,j),and B₃(i,j) are multiplied by respective gain terms 91, 92, 93 byrespective multipliers 61, 71, 81 and summed together with the lowestfrequency band image B₀(i,j) to generated the reconstructed image usingI′. The reconstructed image I′ is defined asI′(i,j)=B ₀(i,j)+g ₁(B ₀(i,j))*B ₁(i,j)+g ₂(B ₀(i,j))*B ₂(i,j)+g ₃(B₀(i,j))*B ₃(i,j)

If the bands are not manipulated, that is ifg₁(B₀(i,j))=g₂(B₀(i,j))=g₃(B₀(i,j))=1.0, the reconstructed image I′ isequal to the original image I, i.e., I′(i,j)=I(i,j).

As shown in FIG. 1 the reconstructed image I′ is mapped through a tonescale (TS) process 90 which maps the values into the desired displayrange. The output image is represented as I″(i,j)=TS(I′(i,j)).

FIG. 2 shows an example of a tone scale function 100 used to map logexposure (x-axis) to optical density (y-axis). It is a sigmoid shape andis parameterized by the minimum density and maximum density, thereference density (or pivot point), the brightness (or shift of tonescale along the log exposure axis relative to the pivot point), and theslope, $\frac{\mathbb{d}D}{\mathbb{d}x},$about the reference density. The reference density maps the log exposurevalue that will remain invariant when the slope of the tone scale isvaried. The brightness control is used to shift the mean density of theimage. The brightness control defines the log exposure code value thatis mapped via the tone scale to the reference density.

FIG. 3 shows the effect of the brightness control (Image A to Image C).Increasing the brightness control lowers the mean density of the image(Image C is lower in mean density than Image A) (or increases thebrightness of the image), while decreasing the brightness control raisesthe mean density of the image (or darkens the image). In a preferredembodiment, the tone scale function is further mapped to a standard grayscale display function (as specified by the Medical Image Standardformat DICOM PART 10) for monochrome image presentation. Thisfacilitates the same gray scale rendering between softcopy (videomonitor) systems and between softcopy and hardcopy (film, paper)systems.

The amount of contrast in which the mid size detail in an image isrendered is defined as the detail contrast. In traditional screen filmradiographic imaging systems, there is an inherent tradeoff betweendetail contrast and latitude (or range of log exposure that are renderedto unique densities). In these systems, if the contrast is increased,the latitude is decreased (or image dynamic range is increased).Likewise, if the latitude is increased, (or image dynamic rangedecreased) the detail contrast is decreased. The same is true if theimage dynamic range and detail-contrast are controlled via a digitalenhancement process (e.g., multi-resolution decomposition) in which theoutput of the process is mapped through a tone scale to render it to thedisplay. Inherently, the tone scale also modifies both the dynamic rangeand detail contrast of an image. As shown in FIG. 4, from image A toimage C as the slope of the tone scale increases both the image dynamicrange and detail-contrast are increased and the latitude is decreased.Unless the digital enhancement process accounts for the tone scaleeffects both the dynamic range and detail-contrast of the image will beaffected upon display.

In the embodiment of the present invention, shown in FIG. 1, the lowestfrequency band of the multi-resolution decomposition is B₀(i,j). If thisband is manipulated it affects the dynamic range of the image. Aspreviously discussed, the slope of the tone scale,$\frac{\mathbb{d}D}{\mathbb{d}x},$also affects the dynamic range.

According to the present invention, the lowest band is not manipulatedfor dynamic range control; instead, the slope of the tone scale is used.The dynamic range control is defined as the slope of the tone scale,dynamicRange=dD/dx at the reference density. Increasing the dynamicrange reduces the latitude while decreasing the dynamic range increasesthe latitude.

Manipulation of band B₁(i,j) affects the detail contrast of the image.According to the present invention, band B₁(i,j) is multiplied by thegain term g₁(B₀(i,j)) at multiplier 61. As previously discussed, theslope of the tone scale also affects the detail contrast of the image.To account for the fact that both the slope of the tone scale$\frac{\mathbb{d}D}{\mathbb{d}x},$and the gain term g₁(B₀(i,j)) affect the detail contrast, a detailcontrast control is defined as adetailContrast(B₀(i,j))=g₁(B₀(i,j))*(dD/dx).

By defining the dynamic range and detail contrast parameters in this wayindependent control of these attributes can be achieved. This isillustrated by FIG. 5. It shows a 3×3 matrix of images (i.e., IA, IB,IC, IIA, IIB, IIC, IIIA, IIIB, IIIC) processed using these controls. Bymoving from left to right (Image A and Image C) across a row (I, II,III) in the matrix, the dynamic range increases as the value of thedynamic range control is increased, while the detail contrast is heldconstant at a particular level. By moving from the bottom to top of thematrix along a column (A, B, C) the detail contrast increases as thevalue of the detail contrast control is increased while the dynamicrange is held constant at a particular level. The image 200 (IA) in thebottom left corner has wide latitude and low detail contrast, while theimage 201 (IIIC) in the upper right corner has narrow latitude and highdetail contrast.

The controls for the sharpness of small features, sharpness(B₀(i,j)),and very fine features, fineDetail(B₀(i,j)), are defined as follows${{sharpness}\quad\left( {B_{0}\left( {i,j} \right)} \right)} = \frac{g_{2}\left( {B_{0}\left( {i,j} \right)} \right)}{g_{1}\left( {B_{0}\left( {i,j} \right)} \right)}$${{fineDetail}\quad\left( {B_{0}\left( {i,j} \right)} \right)} = \frac{g_{3}\left( {B_{0}\left( {i,j} \right)} \right)}{g_{2}\left( {B_{0}\left( {i,j} \right)} \right)}$

To achieve the independent control of sharpness/blurring, it is foundthat controlling the gain ratio between the frequency bands isimportant. The sharpness(B₀(i,j)) parameter provides control of thesharpness of small detail in an image, and the fineDetail(B₀(i,j))parameter provides an extra level of control over the sharpness of veryfine detail in an image.

The gain terms that are used to manipulated the frequency bands, B₁, B₂,and B₃ are derived from detail contrast, sharpness and fine detailcontrols respectively as followsg ₁(B ₀(i,j))=detailContrast(B ₀(i,j))/dD/dxg ₂(B ₀(i,j))=sharpness(B ₀(i,j))*g ₁(B ₀(i,j))g ₃(B ₀(i,j))=fineDetail(B ₀(i,j))*g ₂(B ₀(i,j))

The present invention enables exposure dependent control of thedetailContrast(B₀(i,j)), sharpness(B₀(i,j)), and fineDetail(B₀(i,j)).The low band image B₀(i,j) represents the average log exposure andserves as a map of exposure regions in an image. To achieve exposuredependent control of the image enhancement, the parameters are definedas a function of that band. Areas of the low band image where the codevalues are low correspond to the low exposure regions in the image (thatis the low density or bright areas in the image). Areas where the codevalues are high correspond to high exposure regions in the image (thatis the high density or dark areas in the image). This information can beused to provide exposure dependent control of detail contrast, sharpnessof edges, and sharpness of fine detail and to improve the enhancement ofthe image.

FIGS. 6 a-6 c show examples of a functional form of the detail contrast(FIG. 6 a), sharpness (FIG. 6 b), and fine detail (FIG. 6 c) controls,respectively. In this example the function is constant across allexposure regions (exposure independent). When a control is set to avalue of 1.0 there is no enhancement of features in the image. While acontrol value greater than 1.0 result in the enhancement of features inthe image. Both the sharpness and the fine detail controls can havevalues less than 1.0 (but not negative). If these controls are set to avalue less than 1.0, the corresponding features are blurred (the gain ofthese bands are decreased relative to the lower bands). Setting thefineDetail(B₀(i,j)) control to a value less than 1.0 is used to reducethe appearance of high frequency noise in an image.

FIGS. 7 a-7 c shows an example of an exposure dependent functional formthat can be used for detail contrast, sharpness and fine detailcontrols, respectively. The functional form is a piecewise linear curvein which two breakpoints are used. The function is parameterized bysetting a left and right log exposure break point, and a left functionvalue (for B₀(i,j)<=left break point) and a right function value (forB₀(i,j)>=right break point). The functional form between the breakpointsis linear.

As shown in FIG. 8, breakpoints can be first assigned in density andthen mapped to log exposure breakpoints via the tone scale curve. Thehigh-density breakpoint is mapped to the right log exposure breakpointand the low-density breakpoint is mapped to the left log exposurebreakpoint. Once the brightness and dynamic range of the image are set,via the tone scale, then the log exposure breakpoint are defined.Setting the breakpoint in density provides a mechanism to achieve apreferred rendering of density regions. Often they correspond directlyto important anatomical structures in a radiographic image of anindividual. For example, on a chest image the lung field is a higherdensity (darker) region and can be rendered differently from thediaphragm, which is in a lower density (brighter) region. As illustratedin FIG. 9, a user or image analysis algorithm can independently controlthe detail contrast (as well as sharpness of small and fine detail (ornoise suppression)) in low and high-density areas of an image. Forexample the detail contrast can be set higher in the lung field areas300 and lower in the lower density diaphragm area 301.

It will be evident to those skilled in the art that there are otheruseful functional forms that can be generated for thedetailContrast(B₀(i,j)), sharpness(B₀(i,j)), and fineDetail(B₀(i,j))controls.

Another embodiment of the present invention is shown in FIG. 10. In thisembodiment, the original image I(i,j) from Image acquisition unit 10 andthe low-pass images (and not the frequency band images) (from low passfilter operators 20, 30, 40 are directly manipulated at multipliers 400,401, 402, and 403, and the results are summed together at adders 501,502, and 503 to generated the reconstructed image I′(i,j) which isexpressed asI′(i,j)=g ₃(I ₀(i,j))I(i,j)+(1−g ₁(I ₀(i,j)))I ₀(i,j)+(g ₁(I ₀(i,j))−g₂(I ₀(i,j)))I ₁(i,j)+(g ₂(I ₀(i,j)−g ₃(I ₀(i,j)))I ₂(i,j)

This embodiment produces the same result as the method shown in FIG. 1but does not require the calculation of the frequency band images andmay be advantageous in some implementations.

It is a preferred embodiment of this invention that the brightness anddynamic range parameters and the parameters for thedetailContrast(B₀(i,j)), sharpness(B₀(i,j)), and fineDetail(B₀(i,j))functions be either entered directly at a user interface to thealgorithm or automatically determined via an image analysis method.

Referring now to FIG. 11, there is shown a digital computer 600 forcarrying out the present invention. As shown, digital computer 600includes memory 601 for storing digital images, application programs,operating systems, etc. Memory 601 can include mass memory (such as hardmagnetic disc or CD ROM), and fast access memory (such as RAM). Computer600 also includes input devices 602 (such as keyboard, mouse, touchscreen) display 603 (CRT, Flat Panel Display), central processing unit604, output device 605 (thermal printer, laser printer, etc.).Components 601, 602, 603, 604, and 605 are connected together bycontrol/data bus 606. Computer 600 can include a transportable storagemedium drive 607 for reading from and/or writing to transportablestorage media 608, such as DVD or CD.

The invention has been described in detail with particular reference tocertain preferred embodiments thereof, but it will be understood thatvariations and modifications can be effected within the spirit and scopeof the invention.

Parts List

-   10 image acquisition unit-   20 low-pass operator using filter K₀-   30 low-pass operator using filter K₁-   40 low-pass operator using filter K₂-   60,70,80 subtractor-   61,71,81 multiplier-   62,72,82 adder-   90 tone scale process-   91,92,93 gain terms-   100 example tone scale function-   200 low detail contrast and wide latitude image example-   201 high detail contrast and narrow latitude image example-   300 high-density lung field area-   301 low-density diaphragm area-   400-403 multiplier-   501-503 adder-   600 computer-   601 memory-   602 input device-   603 display-   604 processing unit-   605 output device-   606 control/data bus-   607 transportable storage medium-   608 storage media

1. A method of enhancing a digital image comprising: providing a digitalimage; decomposing the provided digital image into a multi-frequencyband representation including a low frequency band image and multipledifferent high frequency band images; multiplying each of saidhigh-frequency band images with a gain factor; summing together saidunmodified low frequency band image and said modified high-frequencyband images to produce a reconstructed digital image; and mapping saidreconstructed digital image through a tone-scale look-up-table to mapsaid reconstructed digital image to optical densities.
 2. The method ofclaim 1 wherein said providing provides a digital medical image.
 3. Themethod of claim 1 wherein said providing provides a digital radiologicalimage acquired by one of a medical diagnostic imaging unit, a computedradiography unit, a direct digital radiography unit, and an x-ray filmdigitizer.
 4. The method of claim 1 wherein said decomposing is effectedby processing said provided digital image with a plurality of differentlow pass filter operators which operate to pass different low-passimages. Said low-pass images are used to generate said low-frequencyband image and said multiple different high-frequency band images. 5.The method of claim 4 wherein said plurality of low pass filteroperators use square wave filters.
 6. The method of claim 4 wherein saidplurality of different low pass filter operators use different filterkernel sizes to pass said different low-pass images.
 7. The method ofclaim 6 wherein said plurality of different low pass filter operatorsinclude first, second and third pass filter operators having respectivefirst, second and third kernels.
 8. The method of claim 1 wherein saiddecomposing decomposes the provided digital image into four frequencybands as follows: a lowest frequency band image which representslarge-sized features in the digital image; a low-to-mid frequency bandimage which represents mid-sized features in the digital image; amid-to-high frequency band image which represents the small-sizedfeatures in the digital image; and a highest frequency band whichrepresents very fine detail in the digital image.
 9. The method of claim8 including manipulating said lowest frequency band image to produce adynamic range or latitude in said digital image.
 10. The method of claim8 including manipulating said low-to-mid frequency band image to producea contrast effect without affecting the overall dynamic range of saiddigital image.
 11. The method of claim 8 including manipulating saidmid-to-high frequency band image to produce a sharpness or blurringeffect of said small-sized features of said digital image.
 12. Themethod of claim 8 including manipulating the highest frequency bandimage to produce a sharpness or blurring effect of very fine detail insaid digital image.
 13. The method of claim 1 wherein said mappingincludes a brightness control for shifting the mean density of thedigital image.
 14. The method of claim 1 wherein said mapping furtherincludes mapping the tone scale function to a standard gray scaledisplay function for monochrome image presentation.
 15. The method ofclaim 1 wherein in said mapping, said tone scale has slope at areference density that defines dynamic range control and whereinincreasing the dynamic range reduces latitude of said digital image,while increasing the dynamic range decreases the latitude to saiddigital image.
 16. The method of claim 8 wherein said gain factor whichmultiplies said low-to-mid frequency band image is derived from a detailcontrast control and said dynamic range control.
 17. The method of claim8 wherein said gain factor which multiplies said mid-to-high frequencyband image is derived from a sharpness control and said gain factorwhich multiplies said low-to-mid frequency band image.
 18. The method ofclaim 8 wherein said gain factor which multiplies said highest frequencyband image is derived from a fine detail control and said gain factorwhich multiplies the mid-to-high frequency band image.
 19. A method ofenhancing a digital image comprising: providing a digital image;decomposing the provided digital image into a multi-frequencyrepresentation including a low frequency image and multiple differenthigh frequency images; multiplying each of said high frequency imageswith a gain factor; summing together said unmodified low frequency imageand said modified high frequency images to produce a reconstructeddigital image; and mapping said reconstructed digital image through atone scale loop-up-table to map and reconstructed digital image tooptical densities.
 20. The method of claim 8 wherein said gain factorswhich multiply said higher frequency bands are a function of said lowestfrequency band image.
 21. The method of claim 16 wherein said detailcontrast control is a function of said lowest frequency band image(which represents average log exposure).
 22. The method of claim 21wherein the functional form of said detail contrast control is apiecewise linear curve with breakpoints.
 23. The method of claim 22wherein said breakpoints are first assigned in density and then mappedto log exposure breakpoints via said tone scale curve providing densitydependent control of the detail contrast of said image.
 24. The methodof claim 17 wherein the said sharpness control is a function of saidlowest frequency band image (which represents an average log exposure).25. The method of claim 24 wherein the functional form of said sharpnesscontrol is a piecewise linear curve with breakpoints.
 26. The method ofclaim 25 wherein said breakpoints are first assigned in density and thenmapped to log exposure breakpoints via said tone scale curve providingdensity dependent control of the sharpness of small detail of saidimage.
 27. The method of claim 18 wherein said fine detail control is afunction of the lowest frequency band image (which represents an averagelog exposure).
 28. The method of claim 27 wherein the functional form ofsaid fine detail control is a piecewise linear curve with breakpoints.29. The method of claim 28 wherein said breakpoints are first assignedin density and then mapped to log exposure breakpoints via said tonescale curve providing density dependent control of the sharpness of finedetail of said image.
 30. The method of claim 15 wherein manipulation ofsaid dynamic range control does not affect the detail contrast orsharpness of small of fine detail of said image.
 31. The method of claim16 wherein manipulation of said detail contrast control does not affectthe overall dynamic range or sharpness of small or fine detail of saidimage.